1. Knowledge and understanding: The course aims at presenting the principles of econometrics: estimators and their properties; hypothesis testing.
2. Applying knowledge and understanding: The student has to be able to apply the theoretical knowledge acquired in order to analyse the econometric evidence provided in scientific articles, and in order to build a (simple) econometric exercise (multiple regression analysis).
3. Making judgements: The student will be able to understand meaning, role and limits of an econometric model.
4. Communication skills: During the course the student has to improve and develop the knowledge of a technical and economic language; the student has be able to explain (to both experts and laymen) meaning and characteristics of an econometric model.
5. Learning skills: The student will be able to understand which theoretical concept is appropriate to deal with specific problems in econometric modelling.
(1) Introduction to econometrics and its role in the scientific character of economics; (2) The simple linear regression; (3) Interval estimation and hypothesis testing; (4) Multiple regression and OLS; (5) Regressor endogeneity and IV estimator; (6) GLS estimation; (7) Stationary and non-stationary time series; (8) Dynamic specification; (9) VAR and VECM; (10) Qualitative and Limited Dependent Variable Models; (11) econometirc models with financial data with high frequency. Applications - building and evaluating an econometric model: (a) Empirical exercises from the textbook and from the Instructor; (b) critical reading of econometric evidence provided in scientific articles; (c) individual construction and validation of an econometric model.
1. C. HILL - W. E. GRIFFITHS - G.C. LIM, Principles of Econometrics, (Last edition)
As an alternative: . J.H. Stock – M. W. Watson, Introduction to Econometrics, Pearson
2 "Guide to GRETL" (freely downloadable from the web)